Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents

This paper proposes three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We first propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forc...

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Main Authors: Liu, Q., Ye, Mengbin, Qin, J., Yu, C.
Format: Journal Article
Language:English
Published: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC 2019
Subjects:
Online Access:http://purl.org/au-research/grants/arc/DP160104500
http://hdl.handle.net/20.500.11937/84387
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author Liu, Q.
Ye, Mengbin
Qin, J.
Yu, C.
author_facet Liu, Q.
Ye, Mengbin
Qin, J.
Yu, C.
author_sort Liu, Q.
building Curtin Institutional Repository
collection Online Access
description This paper proposes three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We first propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work studying event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities, which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information, and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics that include the vector of gravitational potential forces, an adaptive algorithm is proposed. This requires more information about the agent dynamics but allows for the estimation of uncertain parameters associated with the agent self-dynamics. For each algorithm, a trigger function is proposed to govern the event update times. The controller is only updated at each event, which ensures that the control input is piecewise constant and thus saves energy resources. We analyze each controller and trigger function to exclude Zeno behavior.
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institution Curtin University Malaysia
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language English
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publishDate 2019
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spelling curtin-20.500.11937-843872022-10-27T06:05:40Z Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents Liu, Q. Ye, Mengbin Qin, J. Yu, C. Science & Technology Technology Automation & Control Systems Computer Science, Cybernetics Computer Science Euler-Lagrange dynamics event-based control leader-follower consensus multiagent systems LINEAR MULTIAGENT SYSTEMS TRACKING This paper proposes three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We first propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work studying event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities, which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information, and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics that include the vector of gravitational potential forces, an adaptive algorithm is proposed. This requires more information about the agent dynamics but allows for the estimation of uncertain parameters associated with the agent self-dynamics. For each algorithm, a trigger function is proposed to govern the event update times. The controller is only updated at each event, which ensures that the control input is piecewise constant and thus saves energy resources. We analyze each controller and trigger function to exclude Zeno behavior. 2019 Journal Article http://hdl.handle.net/20.500.11937/84387 10.1109/TSMC.2017.2772820 English http://purl.org/au-research/grants/arc/DP160104500 IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC fulltext
spellingShingle Science & Technology
Technology
Automation & Control Systems
Computer Science, Cybernetics
Computer Science
Euler-Lagrange dynamics
event-based control
leader-follower consensus
multiagent systems
LINEAR MULTIAGENT SYSTEMS
TRACKING
Liu, Q.
Ye, Mengbin
Qin, J.
Yu, C.
Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents
title Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents
title_full Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents
title_fullStr Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents
title_full_unstemmed Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents
title_short Event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents
title_sort event-triggered algorithms for leader-follower consensus of networked euler-lagrange agents
topic Science & Technology
Technology
Automation & Control Systems
Computer Science, Cybernetics
Computer Science
Euler-Lagrange dynamics
event-based control
leader-follower consensus
multiagent systems
LINEAR MULTIAGENT SYSTEMS
TRACKING
url http://purl.org/au-research/grants/arc/DP160104500
http://hdl.handle.net/20.500.11937/84387